1. Field of the Invention
The present invention relates to a sentence forming apparatus, and more particularly, it relates to an apparatus for forming a plurality of semantically equivalent sentences simultaneously in a plurality of languages by a conversational system.
2. Description of the Prior Art
In general, two systems have been proposed in the art for forming sentences. One is called a translation system, in which a sentence of a target language is formed by expressing the object content in a sentence formed by another language, which another language is syntactically analyzed to reconstruct a sentence by the result of the syntax analysis, thereby obtaining the object sentence in the target language. Another system is called a one-to-one coordination system, in which sentences in a target language are formed by preparing sentences in one-to-one coordination with the subject sentences in another language, from which one sentence is selected to partially replace words included therein for obtaining the object sentences. These systems are hereafter explained in further detail.
FIG. 1 is an illustration showing the conventional translation system. An input device 1 is connected to a syntax analyzer 3, which in turn is connected to an internal expression storage control device 4. The internal expression storage control device 4 is connected to a sentence assembler 5, which is connected to an output device 7. An A-language sentence 2 is an input language sentence which is, e.g., a Japanese sentence. A B-language sentence 6 is a target language sentence which is, e.g., an English sentence. The input device 1 comprises a keyboard according to, e.g., Japanese Industrial Standard (SIS) or American Standard Code for Information Interexchange (ASCII), for input operation in a character level. The syntax analyzer 3 syntactically analyzes the A-language sentence 2. The internal expression storage control device 4 stores the result of analysis in the syntax analyzer 3. The sentence assembler 5 assembles a sentence by the data in the internal expression storage control device 4. The output device 7 outputs the sentence assembled in the sentence assembler 5.
The A-language sentence 2 inputted by the keyboard in character units is syntactically analyzed by the syntax analyzer 3, to be converted into an internal expression depending on the device. The converted internal expression is stored in the internal expression storage control device 4. The subject internal expression is then converted into the B-language sentence 6, which in turn is outputted from the output device 7.
Such a conventional translation system has serious disadvantages as follows:
(a) For inputting characters, there has been required, in the keyboard, operation of a plurality of key elements such as alphabet keys, numeral keys and Japanese Kana keys. Such a requirement causes users much trouble in time and operation procedure for inputting a sentence. Particularly for those who are not accustomed to the keyboard arrangement, a rather great effort is required for finding necessary characters on the keyboard.
(b) With respect to the syntax analyzer 3, there are the following disadvantages:
(b.sub.1) Since the A-language sentence is inputted by character columns, there have been indispensably required grammatical analyzing processes such as recognition of words, a "Kiridashi" process (a process for writing the sentence with a space between words), consulting to a dictionary and determination in accidence. However, generally a natural language inputted in the device has, as a matter of course, various sentence structures for expressing the same meaning or purport, diversity of which cannot be processed by the system.
(b.sub.2) When the A-language sentence is still to be analyzed by the conventional translation system, it is necessary to provide the grammatical syntax analyzer with a device for semantic analysis to specify a single meaning or purport from the inputted character columns alone. Further, for operating such a device, a dictionary is required to deal with the character columns formed by the natural language with respect to all things in nature, inevitably leading to incalculable contents of the dictionary.
A problem common in the above items b.sub.1 and b.sub.2 is that it is extremely difficult to extract from the character columns in the A-language sentence, which is already determined in notation, a concept expression involved in the sentence by the analyzer means alone.
Description is now made with respect to the conventional one-to-one coordination system, which is illustrated in FIG. 2. An input device 1 is connected to a retrieving device 9, which in turn is connected to storage devices 11 and 12 as well as to a word substituting device 10. The word substituting device 10 is connected to an output device 7. With respect to difference between the system in FIG. 2 and that shown in FIG. 1, the storage devices 11 and 12 in FIG. 2 are adapted to store sentences having identical contents of expression respectively in an A-language and a B-language in a coordinated manner. In other words, as shown in FIG. 3, a model A.sub.i (i represents an integer selected from 1 to n) in the storage device 11 formed by an sentence or words in the A-language and a model B.sub.i (i represents an integer selected from 1 to n) in the storage device 12 formed by a sentence or words in the B-language are in one-to-one coordination with each other.
The retrieving device 9, which contains means for retrieving a sentence corresponding to an A-language sentence inputted in character units by a keyboard from the storage device 11 or means for successively displaying and selecting respective models A.sub.i in the storage device 11, specifies a model A.sub.1, for selection of a B-language model B.sub.1 which is in one-to-one coordination therewith. The selected B-language model B.sub.1 is subjected to sentence conversion to some extent by substitution of words contained therein by the word substituting device 10. A sentence from the word substituting device 10 is outputted as a B-language sentence from the output device 7.
Such a one-to-one coordination system also has the following disadvantages:
(a) Since this system is based on a requirement for inputting by character columns, there is a disadvantage identical to that pointed out in the above item (a) with respect to the aforementioned translation system.
(b) In general, an inputted natural language (A-language) has various expressions. Therefore, for processing sentence-to-sentence conversion at a level exceeding the function of an electronic dictionary, a great volume of models are required to be stored and retrieved. For satisfying such a requirement, the system needs a storage device in such a large scale that it cannot be packaged in the system in practice and a superhigh-speed retrieving mechanism.
(c) The system basically has no function to make sentences for free expression by a user, since model sentences are already stored and fixed in the storage device.
As a result of our investigation of the prior art, we found the following publications.
The publication, entitled "Transition Net Work Grammar for Natural Language Analysis" published by W. A. Woods, Communications of ACM Vol. 13, No. 10, pages 591-606, October, 1970, discloses the use of augmented transition next work, (ATN) grammars for natural language analysis, which represents a rule of syntax analysis in a transition graph fashion.
The publication "WORD EXPERT PERSING" published by Chuck Rieger and Steve Small, International Joint Conference of Artificial Intelligence '79, proceeding pages 723-728, 1979 discloses an appropriate usage of words structured to a dictionary in order to properly syntax-analyze natural language sentences in various cases, with respect to the respective words. The contents of the dictionary include net work structure and procedural information, unlike a conventional item-entry type.
The paper entitled "AN ENGLISH JAPANESE MACHINE TRANSLATION SYSTEM OF THE TITLES OF SCIENTIFIC AND ENGINEERING PAPERS" published by Makoto Nagao, Junichi Tsuji, Koji Yada and Toshihiro Kakimot, COLLING 82, North-Holland Pub. 1982, pages 245-252 discloses an example of English Japanese translation. The object to be translated is the title sentences of scientific and engineering papers. Sentence structure is analyzed by, for example, transition net work and semantical treatment.